In addition to traditional text-based content, users are increasingly seeking out other forms of relevant content, such as images, videos, and maps. One way that entities such as search companies determine what types of results to provide is to construct whitelists. If the query provided by the user includes a term appearing on a whitelist, then results of the content type for which the whitelist was constructed will be among those returned. For example, a search company might manually maintain a list of celebrities, famous locations, and the names of other things that users might want images of. If a user includes a whitelisted term in a query (e.g., “Coliseum”), a mixture of image and text results will be provided. If the query does not include a word on the whitelist, only text results will be provided. Unfortunately, maintaining a whitelist is typically a cumbersome and error prone process. It is infeasible to list every possible concept in each of the appropriate whitelists. And, if no entry is included in the whitelist for a term, then no image results will be returned even if though relevant images may exist and be desirable to the user. Another approach is to maintain a list of several different content repositories (e.g., a text repository, a video repository, and a photograph repository) and whenever a query is received, to perform a search on each of those repositories. One problem with such an approach is that it requires the maintaining of and access to vast repositories of content. It is also potentially very inefficient. An additional problem with both approaches is that it can be difficult to arranges results of different content types.